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Active Perception Fruit Harvesting Robots — A Systematic Review

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Abstract

This paper studies the state-of-the-art of active perception solutions for manipulation in agriculture and suggests a possible architecture for an active perception system for harvesting in agriculture. Research and developing robots for agricultural context is a challenge, particularly for harvesting and pruning context applications. These applications normally consider mobile manipulators and their cognitive part has many challenges. Active perception systems look reasonable approach for fruit assessment robustly and economically. This systematic literature review focus in the topic of active perception for fruits harvesting robots. The search was performed in five different databases. The search resumed into 1034 publications from which only 195 publications where considered for inclusion in this review after analysis. We conclude that the most of researches are mainly about fruit detection and segmentation in two-dimensional space using evenly classic computer vision strategies and deep learning models. For harvesting, multiple viewpoint and visual servoing are the most commonly used strategies. The research of these last topics does not look robust yet, and require further analysis and improvements for better results on fruit harvesting.

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Funding

The research leading to these results has received funding from National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e Tecnologia and from the European Social fund (FSE), within the scholarship agreement number SFRH/BD/147117/2019. The research leading to these results has also received funding from the European Union’s Horizon 2020 – The EU Framework Programme for Research and Innovation 2014-2020, under grant agreement No. 857202.

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Authors and Affiliations

  1. CRIIS - Centre of Industrial Robotics and Intelligent System, INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Campus da FEUP, Rua Dr. Roberto Frias s/n, 4200-465, Porto, Portugal

    Sandro Augusto Magalhães, António Paulo Moreira & Filipe Neves dos Santos

  2. Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n, 4200-465, Porto, Portugal

    Sandro Augusto Magalhães & António Paulo Moreira

  3. Institute of Systems and Robotics, Department of Electrical Engineering and Computers, University of Coimbra, Rua Silvio Lima – Pólo II, 3030-290, Coimbra, Portugal

    Jorge Dias

  4. Khalifa University Center for Autonomous Robotic Systems (KUCARS), Khalifa University of Science, Technology and Research (KU), Abu Dhabi, 127788, United Arab Emirates

    Jorge Dias

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  1. Sandro Augusto Magalhães
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Contributions

Conceptualization, S.A.M. and F.N.d.S.; data curation, S.A.M.; funding acquisition, S.A.M and F.N.d.S.; investigation, S.A.M.; methodology, S.A.M. ; project administration, S.A.M, F.N.d.S., J.D. and A.P.M; supervision, F.N.d.S., J.D. and A.P.M.; validation, F.N.d.S., J.D. and A.P.M.; writing—original draft, S.A.M.; writing—review and editing, S.A.M., F.N.d.S., J.D. and A.P.M.

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The research leading to these results has received funding from National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e Tecnologia and from the European Social Fund (FSE), within the scholarship agreement number SFRH/BD/147117/2019. The research leading to these results has also received funding from the European Union’s Horizon 2020 - The EU Framework Programme for Research and Innovation 2014-2020, under grant agreement No. 857202.

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Magalhães, S.A., Moreira, A.P., Santos, F.N.d. et al. Active Perception Fruit Harvesting Robots — A Systematic Review. J Intell Robot Syst 105, 14 (2022). https://doi.org/10.1007/s10846-022-01595-3

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